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Record W2049651549 · doi:10.1093/shm/13.2.265

Signs and Senses: Diagnosis and Prognosis in Early Medieval Pulse and Urine Texts

2000· article· en· W2049651549 on OpenAlexaff
Faith Wallis

Bibliographic record

VenueSocial History of Medicine · 2000
Typearticle
Languageen
FieldArts and Humanities
TopicHistory of Medicine Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsJudgementRevelationIntuitionPremisePhilosophyCausality (physics)EpistemologyTheologyPhysics

Abstract

fetched live from OpenAlex

The character of early medieval medical manuscripts makes it difficult to generalize about the nature of medical knowledge in this period. In order to reconstitute one field of medical science, namely diagnosis and prognosis, while avoiding the pitfalls of unjustified generalization, this essay limits itself to reconstructing the understanding of pulse and urine inspection available in a particular place and time: the Italian monastery of Monte Cassino at the end of the first millennium. The available texts reveal little about the rationale behind these bedside techniques; indeed, pulse and urine seem to be signs without any semiotics, any underlying theory. The clue to this paradox is the fact that these texts see pulse and urine as primarily prognostic rather than diagnostic. Prognosis was understood to be analogous to forms of intuition, judgement, revelation, and prophecy that operated outside the logic of causality. Hence a fully rationalized semiotics was not regarded as necessary for effective medical practice.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0030.017
Scholarly communication0.0050.004
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.037
GPT teacher head0.242
Teacher spread0.205 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations107
Published2000
Admission routes1
Has abstractyes

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